The overall goal of this research is to understand quorum sensing: the process of cell-to-cell communication in bacteria. This application will focus on quorum sensing in two related bacteria: Vibrio cholerae, a major human pathogen and the marine-bacteria Vibrio harveyi. The quorum- sensing systems in these bacteria channel multiple quorum-sensing signals into one signaling circuit. At the heart of this circuit are multiple small regulatory RNAs (sRNAs) that mediate the quorum-sensing switch and allow cells to collectively regulate gene expression. The specific goals of this application are (1) to develop a quantitative model for the quorum sensing circuit in V. cholerae and V. harveyi and (2) to develop a new theoretical framework for analyzing how sensory information is integrated by the Vibrio quorum sensing circuit using analytical tools from engineering and physics. Developing a quantitative model and theoretical framework for analyzing information flow will help answer three fundamental questions. (1) How can the Vibrio quorum-sensing network maintain signal-transduction specificity even when multiple signals are transmitted through a shared pathway? (2) What are the comparative advantages for signaling provided by RNA regulators (as opposed to DNA-binding proteins) in the quorum- sensing circuit? (3) What are the major sources of noise in the quorum-sensing circuit and what is the effect of this noise on signaling properties? Answering these questions will contribute to our understanding of intra- and inter-species communication in bacteria and the principles underlying information processing and signaling-transduction in cellular circuits. From a broad modeling perspective, this research is likely to yield new analytic and quantitative tools for analyzing signal-transduction and information flow in biochemical networks. This research also has important health implications because many pathogens such as cholera (Vibrio cholerae) use quorum sensing to regulate virulence. Thus, a greater understanding of quorum-sensing may lead to novel drugs to control infection. ? ? ? ?
| Sgro, Allyson E; Schwab, David J; Noorbakhsh, Javad et al. (2015) From intracellular signaling to population oscillations: bridging size- and time-scales in collective behavior. Mol Syst Biol 11:779 |
| Noorbakhsh, Javad; Schwab, David J; Sgro, Allyson E et al. (2015) Modeling oscillations and spiral waves in Dictyostelium populations. Phys Rev E Stat Nonlin Soft Matter Phys 91:062711 |
| Harcombe, William R; Riehl, William J; Dukovski, Ilija et al. (2014) Metabolic resource allocation in individual microbes determines ecosystem interactions and spatial dynamics. Cell Rep 7:1104-15 |
| Lang, Alex H; Fisher, Charles K; Mora, Thierry et al. (2014) Thermodynamics of statistical inference by cells. Phys Rev Lett 113:148103 |
| Fisher, Charles K; Mehta, Pankaj (2014) Identifying keystone species in the human gut microbiome from metagenomic timeseries using sparse linear regression. PLoS One 9:e102451 |
| Noorbakhsh, Javad; Lang, Alex H; Mehta, Pankaj (2013) Intrinsic noise of microRNA-regulated genes and the ceRNA hypothesis. PLoS One 8:e72676 |
| Reznik, Ed; Mehta, Pankaj; Segrè, Daniel (2013) Flux imbalance analysis and the sensitivity of cellular growth to changes in metabolite pools. PLoS Comput Biol 9:e1003195 |
| Schwab, David J; Baetica, Ania; Mehta, Pankaj (2012) Dynamical quorum-sensing in oscillators coupled through an external medium. Physica D 241:1782-1788 |
| Schwab, David J; Plunk, Gabriel G; Mehta, Pankaj (2012) Kuramoto model with coupling through an external medium. Chaos 22:043139 |
| Mehta, Pankaj; Schwab, David J (2012) Energetic costs of cellular computation. Proc Natl Acad Sci U S A 109:17978-82 |
Showing the most recent 10 out of 17 publications
